TSRUp

2000년 도입 · 논문 1편에서 사용

TSRUp, or Transformation-based Spatial Recurrent Unit p, is a modification of a ConvGRU used in the TriVD-GAN architecture for video generation. It largely follows TSRUc, but computes $\theta$, $u$ and $c$ in parallel given $x\_{t}$ and $h\_{t−1}$, yielding the following replacement for the $c$ update equation: $$ c = \rho\left(W\_{c} \star\_{n}\left[h\_{t-1}; x\_{t}\right] + b\_{c} \right) $$ In these equations $\sigma$ and $\rho$ are the elementwise sigmoid and ReLU functions respectively and the $\star\_{n}$ represents a convolution with a kernel of size $n \times n$. Brackets are used to represent a feature concatenation.

출처: Transformation-based Adversarial Video Prediction on Large-Scale Data

소개 논문: Transformation-based Adversarial Video Prediction on Large-Scale Data